Field of the Invention
The present invention relates to image processing, and particularly relates to, for example, foreground object identification and monitoring.
Description of the Related Art
In image processing, a video refers to a sequence of images, and the images are also referred to as frames. And generally, an image is made up of visual elements, that is to say, the visual elements are visible characteristics contributing to the appearance of an image; wherein one visual element for example could be a pixel, a Discrete Cosine Transform (DCT) block which represents a group of pixels or a super-pixel which represents a group of pixels with the similar attributes (e.g. similar texture, similar color, similar luminance).
During video surveillance, in order to track moving objects or new appeared objects from frame-to-frame, firstly, it is need to detect foreground objects in current frame with reference to the background (i.e. the background image or the background model image) of a video. Wherein, the moving objects and the new appeared objects are the so-called foreground objects in the current frame (i.e. the current image or the foreground image) of the video, and the background is adaptively obtained based on the frames of the video in a certain duration time previous to the current frame. The existing background subtraction techniques are the conventional and effective approaches to detect the foreground objects. However, in actual applications, environmental illumination changes will negatively affect the video surveillance's ability to accurately detect the foreground objects. Wherein, the environmental illumination changes may include, for example, shadows and highlights caused by illumination fluctuations due to lack of ambient light, shadows due to artificial light sources at night, or shadows cast by real objects. Generally, the shadows and highlights caused by the environmental illumination changes will be wrongly detected as the foreground objects (i.e. false foreground objects), since these shadows and highlights differ in appearance from the background.
Therefore, it's necessary that there is a technology which could identify whether the detected foreground objects are the false foreground objects or not. Patent application US2014/0003720 has disclosed a method for removing the false foreground pixels which are caused by environmental illumination changes via analyzing the reflectance of the foreground image. The reflectance is determined based on the foreground image and the background image via the Retinex theory, wherein the background image is used as a proxy for an environmental illuminance component of the foreground image. And the pixels in the foreground image will be determined as the false foreground pixels and will be removed from the foreground image in case the reflectance is less than the predefined threshold value.
However, the accurate reflectance of the foreground image is difficult to be determined via the Retinex theory, therefore, an approximated value which is estimated by using the existed mathematics technology (such as the low frequency filter method) is always used as the reflectance of the foreground image.